About FullStack FullStack is your AI-native engineering partner, built to turn AI capability into certainty. Most companies can demo AI; few can get it to production and prove what it produced. We close that gap with three capabilities, AI built into your products from the start, elite vetted talent who apply it, and transparent execution that shows value every step of the way. With now over 600 customers in North America, FullStack is one integrated partner for all your AI engineering needs. With FullStack, you move forward with confidence. We’re Most Proud Of Offering life-changing career opportunities to talented software professionals across the Americas. Building highly-skilled software development teams for hundreds of the world’s greatest companies. Having delivered hundreds of successful custom software solutions, which have positively impacted the lives and careers of millions of users. Our 4.1-star rating on GlassDoor. Our client Net Promoter Score of 68, twice the industry average. The Position We're Looking To Hire a Senior Machine Learning Engineer (Traditional ML & Financial Data) To Join Our Team. You'll Work With Our Incredible Clients In One Of Two Ways Team Augmentation: You will integrate yourself directly into our client's team and work alongside their existing designers and engineers on a daily basis. Design & Build: You will work on a FullStack product team to build and deliver a product to our clients. What We're Looking For 5+ years of professional experience in software development, Data Science, or Machine Learning Engineering. Advanced English is required. Successful completion of a four-year college degree is required. Strong expertise in traditional machine learning algorithms and statistical modeling, with a focus on non-LLM and non-Generative AI approaches. Hands-on experience designing, developing, training, and optimizing machine learning models for production use. Strong proficiency in data exploration, preprocessing, feature engineering, and model training using complex datasets. Demonstrated experience developing and optimizing anomaly detection algorithms to identify irregularities, patterns, and outliers in data. Strong Python skills and experience with relevant machine learning and data science libraries. Experience analyzing financial, payroll, or other structured business datasets is highly preferred. Proactive, ownership-driven mindset with strong analytical and problem-solving skills, capable of translating complex data into reliable machine learning solutions. Ability to work through new and difficult issues and contribute to libraries as needed. Ability to create and maintain continuous integration and delivery of applications. Forensic attention to detail. A positive mindset and a can-do attitude. Experience working on Agile/Scrum teams. Meaningful experience working on large, complex systems. Ability to take extreme ownership over your work. Every day is a challenge to ensure you are performing to the expectations you and your team have agreed upon. Ability to identify with the goals of FullStack's clients, and dedicate yourself to delivering on the commitments you and your team make to them. Nice To Have We’re Seeking Engineers Who Are AI-enthusiastic In Their Workflow. Professional Experience Or Personal Project Work With The Following Is a Significant Plus Cursor, Windsurf, or Google Antigravity. Claude Code, Gemini CLI, Codex, or Copilot CLI. Work Authorization Requirements Applicants must be currently authorized to work in the United States on a full-time basis. FullStack will not sponsor applicants for work visas now or in the future.

What We Offer

Competitive Salary. Paid Time Off (vacation, sick leave, parental leave, and holidays). 100% remote work. The ability to work with leading startups and Fortune 500 companies. Health, dental, and vision insurance. 401(k) w/ 4% match. Ample opportunity for career advancement. Continuing education opportunities. FullStack is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Learn more about our Applicants Privacy Notice.